Attitude sensors that measure and output pitch and roll are used for a wide variety of sensing and control applications. A common implementation consists of a minimum of three accelerometers whose sensitive axes are not co-linear, most typically a set of three accelerometers arranged in a nominally orthogonal configuration, known as a triaxial accelerometer. The three accelerometers have a nonzero DC response such that when the sensor is at rest, the projection of the static gravitational acceleration vector onto each of the three accelerometers is measured. From these values, the pitch and roll of the attitude sensor and the magnitude of the gravitational acceleration vector can be determined.
A bias error in one or more of the three accelerometers will manifest as errors in the pitch, roll and gravitational magnitude estimates. Accelerometer bias error is routinely calibrated out under controlled conditions, but many accelerometers, in particular those based on MEMS, exhibit bias drift over time. For certain applications, accelerometer bias that accumulates post-calibration results in unacceptable errors in roll and pitch.
One important example of such an application is magnetic heading measurement at high latitudes. A non-gimbaled magnetic heading sensor incorporating a triaxial magnetometer requires a pitch and roll sensor to calculate the projection of the magnetic vector on the horizontal plane. At high latitudes, the strength of the vertical magnetic field can be more than ten times that of the horizontal magnetic field, so even small errors in pitch and roll introduce large errors in magnetic heading.
Accordingly, a need exists for an alternative accelerometer-based attitude sensor that automatically estimates accelerometer bias on an ongoing basis and applies correction factors to effectively eliminate that bias.